In the seismic processing industry, it is often required to simultaneously process multiple datasets at a time. In a time-lapse context, the main interest is measuring changes in the subsurface conditions to guide infill well drilling and maximize oil and gas production. Often between seismic datasets from any two seismic survey vintages, source and receiver positions are not the same. The seismic survey vintages may be several years apart, and the survey methods used for each vintage may be different. For example one vintage is from a Towed Streamer (TS) seismic survey, and the other vintage is from an Ocean Bottom Cable (OBC) seismic survey. Changes in time and survey methods result in different seismic data acquiring geometries and parameters that can mask the true changes in the subsurface, i.e., the 4D signal, if taken into account when processing the seismic data from multiple vintages.
Previous attempts to compensate for these differences in acquiring geometries and parameters applied a seismic processing sequence that matched seismic datasets from different vintages such that only real subsurface changes were preserved. The seismic processing sequence included 4D binning (e.g. Calvert, 2005), regularization (e.g. Poole and Lecerf, 2006) and migration (e.g. Zhang et al., 2003). These three steps minimized acquisition induced differences (4D noise) while retaining the real 4D signal.
In the 4D binning process, traces are paired from different datasets according to the geometrical differences and possibly other criteria such as normalized root mean square (NRMS) to define a measure of repeatability. Traces with low metric values are dropped. While this approach improves the overall repeatability, the resolution and signal-to-noise ratio are reduced. All seismic datasets are then regularized and imaged independently to the same reference geometry where further processing can be performed. Regularization and migration operators, however, are not perfect and are affected by the geometrical characteristics of the datasets being processed. As these two steps are performed in a dataset independent manner, the geometrically induced imprint is left on the datasets. This can lead to suboptimal results in the differencing process with residual noise potentially masking the 4D signal.
The need still exists, however, for a more accurate determination of changes in the actual traces between two vintages of seismic datasets that compensates for changes in acquisition parameters and acquisition geometries between the two vintages.